
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))


# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "54"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder


# Use environment variables to figure out path to the csvs and auto_metrics
antenna = os.environ["ANTENNA"]
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "178"
csv_folder = "/home/obs/src/H5C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H5C_Notebooks/auto_metrics_inspect"


display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))


import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna


# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, '*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 100 csvs in /home/obs/src/H5C_Notebooks/_rtp_summary_
Found 96 auto_metrics notebooks in /home/obs/src/H5C_Notebooks/auto_metrics_inspect


# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'


this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        antnum = row['Ant']
        if antnum != int(antenna):
            continue
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break


# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])


display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))


html_to_display = ''
for am_html in auto_metric_htmls:
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line: 
            break


HTML(html_to_display)

JDs	A Priori Status	Auto Metrics Flags	Dead Fraction in Ant Metrics (Jee)	Dead Fraction in Ant Metrics (Jnn)	Crossed Fraction in Ant Metrics	Flag Fraction Before Redcal	Flagged By Redcal chi^2 Fraction	ee Shape Modified Z-Score	nn Shape Modified Z-Score	ee Power Modified Z-Score	nn Power Modified Z-Score	ee Temporal Variability Modified Z-Score	nn Temporal Variability Modified Z-Score	ee Temporal Discontinuties Modified Z-Score	nn Temporal Discontinuties Modified Z-Score	Average Dead Ant Metric (Jee)	Average Dead Ant Metric (Jnn)	Average Crossed Ant Metric	Median chi^2 Per Antenna (Jee)	Median chi^2 Per Antenna (Jnn)
2459594	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.264867	-0.878798	3.897358	1.421008	2.259878	4.015424	3.145342	0.252454	0.7601	0.7754	0.2592	15.608104	15.450163
2459593	digital_ok	0.00%	0.00%	0.00%	0.00%	2.69%	2.69%	-0.617793	-1.357052	3.196807	-0.117452	-0.284918	-0.228656	2.979521	0.211404	0.7330	0.7277	0.2598	1.809792	1.888746
2459592	digital_ok	0.00%	100.00%	100.00%	0.00%	-	-	0.146763	-0.578752	0.954144	-0.609889	-1.009322	-0.539506	-1.819315	-0.103051	0.0294	0.0292	0.0010	nan	nan
2459591	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.752904	-0.613452	4.345373	0.355788	-0.142571	-0.846532	-0.510920	-0.483574	0.6570	0.6766	0.3790	5.135656	5.312675
2459590	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.865653	-0.984785	3.955491	-0.342272	-0.884175	0.813508	-0.151668	-0.688500	0.6599	0.6759	0.3757	5.198700	5.380994
2459589	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-1.206174	-1.510521	3.594066	1.223510	1.215275	4.600547	3.648269	0.001860	0.6885	0.6923	0.3033	6.194746	6.650949
2459588	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.744850	-1.326493	4.323374	-0.211966	-0.350968	-1.180223	2.454961	0.245805	0.7764	0.7631	0.2230	7.618373	6.249023
2459587	digital_ok	100.00%	-	-	-	100.00%	0.00%	-0.254856	-0.496312	5.694133	0.950558	0.282681	-0.802341	0.346972	-0.363952	nan	nan	nan	0.000000	0.000000
2459586	digital_ok	0.00%	0.00%	0.00%	0.00%	7.03%	0.00%	-0.947833	-0.579486	-0.844451	-0.542063	0.009684	-0.080715	-0.666931	-1.011804	0.6363	0.6542	0.3806	1.513218	1.566228
2459585	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.800173	-0.485073	-0.748295	-0.863963	-0.725511	-0.271468	-1.073144	-0.675169	0.0364	0.0350	0.0015	0.000000	0.000000
2459584	digital_ok	0.00%	0.00%	0.00%	0.00%	62.28%	4.79%	-1.029602	0.821083	0.474545	-0.891708	-0.863422	1.183821	0.128070	-0.312903	0.5998	0.6176	0.3709	0.946169	0.873929
2459583	digital_ok	0.00%	0.00%	0.00%	0.00%	3.23%	0.00%	-1.134451	-0.572101	-0.301509	-0.853450	-1.094979	-0.569543	-0.721504	-0.787916	0.6566	0.6760	0.3927	1.419160	1.449746
2459582	digital_ok	0.00%	0.00%	0.00%	0.00%	2.70%	0.00%	-0.610944	0.033563	-0.416784	-0.743796	-0.847295	-0.401145	-0.798845	-0.824487	0.6580	0.6758	0.3953	1.358958	1.351561
2459581	digital_ok	0.00%	0.00%	0.00%	0.00%	3.24%	0.00%	-1.310231	-0.214385	-0.004870	-0.850865	-1.019916	-0.471117	-0.540887	-0.855260	0.6616	0.6794	0.3923	1.521696	1.522688
2459580	digital_ok	0.00%	0.00%	0.00%	0.00%	3.76%	0.00%	-0.968726	-0.205433	-0.544089	-0.743703	-1.047508	-0.199895	-0.796860	-0.958931	0.6595	0.6774	0.3907	1.357190	1.395549
2459579	digital_ok	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.557967	0.004664	-0.171715	-0.726402	-1.123615	-0.412091	-0.474200	-0.673817	0.6465	0.6660	0.4008	0.000000	0.000000
2459578	digital_ok	0.00%	100.00%	100.00%	0.00%	-	-	-0.705903	0.152467	-0.606854	-0.372366	-1.206369	-1.094255	0.014886	-0.946265	0.0336	0.0316	0.0012	nan	nan
2459577	digital_ok	0.00%	0.00%	0.00%	0.00%	5.95%	15.14%	-0.982588	-0.856653	-0.039852	-0.873324	-1.067980	-1.091996	-0.527560	-0.865798	0.6586	0.6771	0.3905	1.399325	1.353555
2459576	digital_ok	0.00%	0.00%	0.00%	0.00%	4.84%	0.54%	-1.030995	-0.758565	0.104517	-0.570142	-0.626436	-1.117372	-0.225666	0.288380	0.6824	0.6995	0.3942	1.358717	1.335239
2459575	digital_ok	0.00%	0.00%	0.00%	0.00%	5.91%	0.00%	-0.768725	-0.778927	-0.331476	-0.594454	-1.193386	2.542091	-0.296846	-0.728421	0.7361	0.7455	0.3439	1.483117	1.576985
2459574	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.493628	-0.500070	-0.149983	-0.918962	-0.348352	5.232775	-0.653982	-0.227904	0.6808	0.6984	0.3900	3.830729	3.618671
2459573	digital_ok	0.00%	0.00%	0.00%	0.00%	3.78%	0.00%	-0.898940	-0.136213	-0.276781	-0.594027	-1.560371	-0.974376	-0.701602	-0.534348	0.6747	0.6955	0.3955	1.443380	1.388454
2459572	digital_ok	0.00%	0.00%	0.00%	0.00%	3.78%	0.00%	-1.003942	-0.757840	-0.171931	-0.817415	-0.992329	-1.025035	-0.047542	-0.149186	0.6838	0.7016	0.3917	1.457290	1.494101
2459571	digital_ok	100.00%	100.00%	100.00%	0.00%	-	-	-0.479899	0.187796	-0.791010	-0.420862	-1.186014	14.274743	0.154912	-0.431139	0.0339	0.0301	0.0010	nan	nan
2459570	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	6.507781	6.025206	8.701464	7.352071	5.779424	3.934589	3.958728	4.304094	0.6788	0.7101	0.3770	11.037998	12.237676
2459569	digital_ok	0.00%	0.00%	0.00%	0.00%	4.32%	0.00%	-0.984764	-0.908055	-0.113015	-0.758958	-0.015672	3.127426	-0.022409	-0.591121	0.7420	0.7519	0.2578	1.840562	1.817487
2459566	digital_ok	0.00%	0.00%	0.00%	0.00%	4.32%	0.00%	-0.864425	-0.718389	-0.032796	-0.846928	-0.985452	-0.959350	0.511306	-0.757187	0.6670	0.6861	0.4102	1.495701	1.615919
2459565	digital_ok	0.00%	-	-	-	86.67%	0.00%	-0.056602	-0.056602	-0.073735	-0.073735	0.553413	0.553413	0.061081	0.061081	nan	nan	nan	0.000000	0.000000
2459564	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-1.967491	-1.577508	-4.849810	-4.317832	9.215395	8.403724	-0.360238	-0.761124	0.6732	0.6846	0.4038	2.862080	2.884408
2459563	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	5.641812	6.367175	21.972560	22.710191	11.492568	14.222018	-1.462397	-1.872537	0.6712	0.6805	0.3954	3.726835	3.291207
2459562	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459561	digital_ok	0.00%	0.00%	0.00%	0.00%	4.86%	0.00%	-1.252775	-1.004652	-0.003948	-0.426674	0.003372	-0.141197	0.049368	-0.350609	0.6860	0.7023	0.3948	1.580598	1.586555
2459560	digital_ok	0.00%	0.00%	0.00%	0.00%	4.86%	0.00%	-1.087873	-0.986288	0.249288	-0.403657	0.064012	-0.237071	-0.034195	-0.433236	0.6809	0.6985	0.4074	1.496465	1.440479
2459559	digital_ok	0.00%	0.00%	0.00%	0.00%	5.38%	0.00%	0.170517	0.755654	-0.108234	0.245913	-0.958708	-0.454226	-1.060723	-1.412039	0.6675	0.6826	0.3963	1.536452	1.548078
2459558	digital_ok	0.00%	0.00%	0.00%	0.00%	13.44%	0.54%	-1.025855	-0.438215	-0.474719	-0.751505	-1.241328	-1.011998	-0.041748	-0.715457	0.6748	0.6871	0.4109	1.516694	1.426986
2459557	digital_ok	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0297	0.0292	0.0012	nan	nan
2459556	digital_ok	0.00%	0.00%	0.00%	0.00%	4.86%	0.54%	-0.926564	-0.585760	-0.454048	-0.884402	-1.171658	-1.042593	-0.118630	-0.727148	0.6763	0.6893	0.3991	1.539032	1.408053
2459554	digital_ok	-	0.00%	0.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.6856	0.6990	0.4087	nan	nan
2459553	digital_ok	-	0.00%	0.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.6802	0.6953	0.4079	nan	nan
2459552	digital_ok	0.00%	0.00%	0.00%	0.00%	4.86%	0.00%	-1.140664	-0.686081	-0.094865	1.055596	-1.394853	3.892724	0.231935	0.371621	0.6901	0.7029	0.4003	1.408832	1.490839
2459551	digital_ok	0.00%	0.00%	0.00%	0.00%	5.38%	0.00%	-1.126706	-0.998540	0.152473	-0.424008	0.267674	-0.117403	-0.009298	-0.263059	0.6827	0.6974	0.4013	1.487449	1.484192
2459550	digital_ok	-	99.18%	99.18%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0328	0.0314	0.0008	nan	nan
2459549	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459542	digital_ok	0.00%	0.00%	0.00%	0.00%	22.32%	0.00%	-0.632061	-0.358184	0.940822	-0.557833	-0.434804	-0.689673	-0.162028	-0.838794	0.7315	0.7307	0.3757	1.491165	1.446864
2459541	digital_ok	0.00%	1.34%	1.34%	0.00%	21.88%	0.00%	-0.967740	-0.942511	-0.434288	-1.144877	-0.673373	0.770085	0.616134	-0.036568	0.7215	0.7207	0.3505	1.470074	1.475564
2459540	digital_ok	0.00%	0.00%	0.00%	0.00%	21.88%	0.00%	-1.284548	-1.218104	-0.127052	-0.486255	-0.339014	0.664502	0.014218	-0.370156	0.7365	0.7330	0.3610	1.469134	1.489745
2459536	digital_ok	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-1.490899	-1.187385	0.692919	-0.998443	-0.010562	-1.252764	0.696853	-0.398417	0.7055	0.7136	0.4394	0.000000	0.000000
2459535	digital_ok	0.00%	0.00%	0.00%	0.00%	21.43%	0.00%	-0.891479	-1.059755	0.056771	-0.467330	0.530243	1.555316	0.156234	-0.288089	0.7766	0.7581	0.3769	1.561819	1.515764
2459534	digital_ok	0.00%	0.00%	0.00%	0.00%	20.98%	0.00%	-1.158807	-1.225941	0.047715	-0.594255	0.938014	1.299574	-0.132104	-0.485439	0.7687	0.7501	0.3690	1.507100	1.496405
2459533	digital_ok	0.00%	0.00%	0.00%	0.00%	4.89%	0.00%	-0.857723	-0.666526	-0.511101	-0.457724	-1.257952	-0.438289	-0.742287	-0.572756	0.7064	0.7137	0.4122	1.575977	1.491265
2459532	digital_ok	0.00%	0.00%	0.00%	0.00%	5.00%	0.00%	-0.967224	-0.411042	-0.174062	-0.868547	-1.116451	-0.850176	-0.006337	-0.091791	0.7076	0.7153	0.4101	1.552028	1.534640
2459530	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459527	digital_ok	0.00%	-	-	-	100.00%	0.00%	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459524	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459523	digital_ok	100.00%	-	-	-	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459522	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459513	digital_ok	0.00%	100.00%	100.00%	0.00%	-	-	-0.387721	0.136866	-0.528285	-0.799684	-0.486513	-0.347490	0.009581	0.037879	0.0364	0.0342	-0.0002	nan	nan
2459508	digital_ok	0.00%	0.00%	0.00%	0.00%	81.58%	0.00%	-1.083241	-0.773478	-0.991758	-0.698538	-1.201316	-1.099349	0.300239	-0.590702	0.8993	0.9237	0.2134	0.000000	0.000000
2459505	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-1.000303	-0.562845	-0.115533	-0.536532	-1.407018	-0.622185	-1.186869	-0.774197	0.0691	0.0618	0.0035	0.887578	0.887989
2459503	digital_ok	0.00%	0.00%	0.00%	0.00%	89.47%	0.00%	-1.145088	-0.913890	-0.372471	-0.598972	-0.294087	-1.477385	-0.285965	-0.837723	0.8695	0.8560	0.4538	0.000000	0.000000
2459501	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.617226	-0.277467	-0.972679	0.012895	-0.713136	0.053268	0.335907	-0.838843	0.1080	0.1006	0.0117	0.000000	0.000000
2459500	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.976625	0.002313	-1.264509	0.153680	-0.861300	-0.704561	0.204731	-0.607562	0.0949	0.1059	0.0099	0.000000	0.000000
2459499	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.854856	-0.405454	-1.341159	-0.115383	-0.920271	-0.870743	0.012622	-0.496056	0.1014	0.1206	0.0083	0.000000	0.000000
2459498	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	9.038181	-0.539140	4.199537	-0.160759	9.829482	-0.935737	32.558485	-0.662824	0.0423	0.0883	0.0042	0.000000	0.000000
2459497	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-1.203768	-0.612704	-1.129093	-0.169958	-1.246679	-1.233357	-0.838656	-0.693816	0.0990	0.1089	0.0102	0.000000	0.000000
2459496	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-1.179256	-0.972234	-0.822678	-0.202560	-0.646579	-1.637059	-0.493397	-0.674863	0.0891	0.1067	0.0097	0.000000	0.000000
2459495	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-1.142391	-0.649602	-0.710954	-0.190847	-0.668476	-1.214924	-0.642516	-0.722578	0.1079	0.1054	0.0130	0.000000	0.000000
2459494	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.861414	-0.477691	-1.045254	-0.071634	-1.024322	-1.302545	-0.796685	-0.844916	0.1129	0.1167	0.0135	0.000000	0.000000
2459492	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.779231	-0.448952	-1.062479	-1.348657	-0.392165	-0.065855	-0.373807	-0.779046	0.0949	0.0732	0.0060	0.000000	0.000000
2459491	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.401764	-0.572334	-0.716919	-1.514164	-0.261693	0.049396	-0.971667	-0.980944	0.1036	0.0929	0.0064	0.000000	0.000000
2459490	digital_ok	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.724436	-0.357531	-1.036946	-1.935719	-0.307471	-0.396131	-0.759427	-0.453810	0.7386	0.8013	0.3717	0.000000	0.000000
2459489	digital_ok	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.621427	-0.660783	-1.002766	-1.696301	-0.614447	0.522826	-0.035050	1.208730	0.7588	0.8099	0.3215	0.000000	0.000000
2459488	digital_ok	0.00%	0.00%	0.00%	0.00%	85.71%	9.52%	-0.549319	-0.585209	-0.629543	-0.823273	-0.594944	-0.598066	0.009222	-1.083086	0.7586	0.8115	0.3500	0.000000	0.000000

Antenna Season Report Notebook¶

Antenna 178 Report

Load relevant info from summary CSVs¶

Table 1: Per-Night RTP Summary Info For This Atenna¶

Antenna 178, Node 12:

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

Antenna 178: 2459624

Antenna 178: 2459623

Antenna 178: 2459622

Antenna 178: 2459621

Antenna 178: 2459620

Antenna 178: 2459619

Antenna 178: 2459618

Antenna 178: 2459617

Antenna 178: 2459616

Antenna 178: 2459615

Antenna 178: 2459614

Antenna 178: 2459613

Antenna 178: 2459612

Antenna 178: 2459611

Antenna 178: 2459610

Antenna 178: 2459609

Antenna 178: 2459608

Antenna 178: 2459607

Antenna 178: 2459605

Antenna 178: 2459604

Antenna 178: 2459603

Antenna 178: 2459602

Antenna 178: 2459598

Antenna 178: 2459597

Antenna 178: 2459596

Antenna 178: 2459595

Antenna 178: 2459594

Antenna 178: 2459593

Antenna 178: 2459592

Antenna 178: 2459591

Antenna 178: 2459590

Antenna 178: 2459589

Antenna 178: 2459588

Antenna 178: 2459587

Antenna 178: 2459586

Antenna 178: 2459585

Antenna 178: 2459584

Antenna 178: 2459583

Antenna 178: 2459582

Antenna 178: 2459581

Antenna 178: 2459580

Antenna 178: 2459579

Antenna 178: 2459578

Antenna 178: 2459577

Antenna 178: 2459576

Antenna 178: 2459575

Antenna 178: 2459574

Antenna 178: 2459573

Antenna 178: 2459572

Antenna 178: 2459571

Antenna 178: 2459570

Antenna 178: 2459569

Antenna 178: 2459566

Antenna 178: 2459565

Antenna 178: 2459564

Antenna 178: 2459563

Antenna 178: 2459562

Antenna 178: 2459561

Antenna 178: 2459560

Antenna 178: 2459559

Antenna 178: 2459558

Antenna 178: 2459556

Antenna 178: 2459552

Antenna 178: 2459551

Antenna 178: 2459549

Antenna 178: 2459542

Antenna 178: 2459541

Antenna 178: 2459540

Antenna 178: 2459536

Antenna 178: 2459535

Antenna 178: 2459534

Antenna 178: 2459533

Antenna 178: 2459532

Load antenna metric spectra and waterfalls from `auto_metrics` notebooks.¶